Designing across domains with declarative thinking: Insights from the 96-Eyes ptychographic imager project

Fuente: arXiv
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Main Author: Chan, Antony C
Format: Preprint
Published: 2025
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author Chan, Antony C
author_facet Chan, Antony C
contents This article presents a practitioner's reflection on applying declarative, 5th generation, problem formulation language (5GL) to de novo imaging system design, informed by experiences across the interdisciplinary research in academia and cross-functional product development within the private sector. Using the 96-Eyes project: 96-camera parallel multi-modal imager for high-throughput drug discovery as a representative case, I illustrate how project requirements, ranging from hardware constraints to life sciences needs, can be formalized into machine-readable problem statements to preserve mission-critical input from diverse domain stakeholders. This declarative approach enhances transparency, ensures design traceability, and minimizes costly misalignment across optical, algorithmic, hardware-accelerated compute, and life sciences teams. Alongside the technical discussion of 5GL with real-world code examples, I reflect on the practical barriers to adopting 5GL in environments where imperative, 3rd-generation languages (3GL) remain the default medium for inter-team collaboration. Rather than offering an one-size-fits-all solution, these learned lessons highlight how programming paradigms implicitly shapes research workflows through existing domain hierarchies. The discussion aims to invite further explorations into how declarative problem formulations can facilitate innovation in settings where concurrent R\&{}D workflows are gaining traction, as opposed to environments where sequential, phase-driven workflows remain the norm.
format Preprint
id arxiv_https___arxiv_org_abs_2508_18512
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Designing across domains with declarative thinking: Insights from the 96-Eyes ptychographic imager project
Chan, Antony C
Optics
Computation and Language
This article presents a practitioner's reflection on applying declarative, 5th generation, problem formulation language (5GL) to de novo imaging system design, informed by experiences across the interdisciplinary research in academia and cross-functional product development within the private sector. Using the 96-Eyes project: 96-camera parallel multi-modal imager for high-throughput drug discovery as a representative case, I illustrate how project requirements, ranging from hardware constraints to life sciences needs, can be formalized into machine-readable problem statements to preserve mission-critical input from diverse domain stakeholders. This declarative approach enhances transparency, ensures design traceability, and minimizes costly misalignment across optical, algorithmic, hardware-accelerated compute, and life sciences teams. Alongside the technical discussion of 5GL with real-world code examples, I reflect on the practical barriers to adopting 5GL in environments where imperative, 3rd-generation languages (3GL) remain the default medium for inter-team collaboration. Rather than offering an one-size-fits-all solution, these learned lessons highlight how programming paradigms implicitly shapes research workflows through existing domain hierarchies. The discussion aims to invite further explorations into how declarative problem formulations can facilitate innovation in settings where concurrent R\&{}D workflows are gaining traction, as opposed to environments where sequential, phase-driven workflows remain the norm.
title Designing across domains with declarative thinking: Insights from the 96-Eyes ptychographic imager project
topic Optics
Computation and Language
url https://arxiv.org/abs/2508.18512